Wind noise is defined herein as a microphone signal generated from turbulence in an air stream flowing past a microphone port or over a microphone membrane. This is as opposed to the sound of wind blowing past other objects distal from the microphone, such as the sound of rustling leaves as wind blows past a tree in the far field, and such distal noise sources do not comprise wind noise within the present definition.
For wearable devices, the proximity of a human body (e.g. head, torso, and/or hand) may generate additional turbulence and wind noise. Wind noise is impulsive and often has an amplitude large enough to exceed the nominal speech amplitude. Wind noise can thus be objectionable to the user and/or can mask other signals of interest. It is desirable that digital signal processing devices are configured to take steps to ameliorate the deleterious effects of wind noise upon signal quality. To do so requires a suitable means for reliably measuring wind noise when it occurs, without falsely indicating that wind noise exists to some extent when in fact other factors are affecting the signal.
Some previous approaches to wind noise detection (WND) assume that non-wind sounds are generated in the far field and thus have a similar sound pressure level (SPL) and phase at each microphone, whereas wind noise is substantially uncorrelated across microphones. However, for non-wind sounds generated in the far field, the SPL between microphones can substantially differ due to localized sound reflections, room reverberation, and/or differences in microphone coverings, obstructions, or location such as due to orthogonal plane placement of microphones on a smartphone with one looking inwards and the other looking outwards. Substantial SPL differences between microphones can also occur with non-wind sounds generated in the near field, such as a telephone handset held close to the microphones. Differences in microphone output signals can also arise due to differences in microphone sensitivity, i.e. mismatched microphones, which can be due to relaxed manufacturing tolerances for a given model of microphone, or the use of different models of microphone in a system.
The spacing between the microphones causes non-wind sounds to have different phase at each microphone sound inlet, unless the sound arrives from a direction where it reaches both microphones simultaneously. In directional microphone applications, the axis of the microphone array is usually pointed towards the desired sound source, which gives the worst-case time delay and hence the greatest phase difference between the microphones.
When the wavelength of a received sound is much greater than the spacing between microphones, i.e. at low frequencies, the microphone signals are fairly well correlated and previous WND methods might not falsely detect wind at such frequencies. However, when the received sound wavelength approaches the microphone spacing, the phase difference causes the microphone signals to become less correlated and non-wind sounds can be falsely detected as wind. The greater the microphone spacing, the lower the frequency above which non-wind sounds will be, or might be, falsely detected as wind, i.e. the greater the portion of the audible spectrum in which false detections might occur. False detection may also occur due to other causes of phase differences between microphone signals, such as localized sound reflections, room reverberation, and/or differences in microphone phase response or inlet port length. Given that the spectral content of wind noise at microphones can extend from below 100 Hz to above 10 kHz depending on factors such as the hardware configuration, the presence of a user's head or hand, and the wind speed, it is desirable for wind noise detection to operate satisfactorily throughout much if not all of the audible spectrum, so that wind noise can be detected and suitable suppression means activated only in sub bands where wind noise is problematic.
In light of the above-noted difficulties of differentiating wind noise from other signal types, to date wind noise has been addressed by coarse detection methods, being systems which simply output a binary flag indicating whether wind noise is present or absent. In such systems the binary output detection flag is then used to alter the operation of other processing modules, such as to switch wind noise reduction on or off in a binary manner. To even produce such a binary detection output is nevertheless difficult to accomplish with sufficient accuracy, due to the complexities noted above.
Any discussion of documents, acts, materials, devices, articles or the like which has been included in the present specification is solely for the purpose of providing a context for the present invention. It is not to be taken as an admission that any or all of these matters form part of the prior art base or were common general knowledge in the field relevant to the present invention as it existed before the priority date of each claim of this application.
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In this specification, a statement that an element may be “at least one of” a list of options is to be understood that the element may be any one of the listed options, or may be any combination of two or more of the listed options.